library(tidyverse)
library(sf)
library(readr)
library(mapview)
Rxdeploy <- read_csv("../data/deployments.csv") #receiver station info
head(Rxdeploy)
## # A tibble: 6 x 23
## station glatos_array station_no consecutive_dep… intend_lat intend_long
## <chr> <chr> <dbl> <dbl> <lgl> <lgl>
## 1 WHT-009 WHT 9 1 NA NA
## 2 FDT-001 FDT 1 2 NA NA
## 3 FDT-004 FDT 4 2 NA NA
## 4 FDT-003 FDT 3 2 NA NA
## 5 FDT-002 FDT 2 2 NA NA
## 6 DTR-001 DTR 1 2 NA NA
## # … with 17 more variables: deploy_lat <dbl>, deploy_long <dbl>,
## # recover_lat <lgl>, recover_long <lgl>, deploy_date_time <dttm>,
## # recover_date_time <dttm>, bottom_depth <dbl>, riser_length <dbl>,
## # instrument_depth <dbl>, ins_model_no <chr>,
## # glatos_ins_frequency <dbl>, ins_serial_no <dbl>, deployed_by <lgl>,
## # comments <lgl>, glatos_seasonal <chr>, glatos_project <chr>,
## # glatos_vps <chr>
rec_sf <-
Rxdeploy %>%
st_as_sf(coords = c("deploy_long", "deploy_lat")) ## specify which columns contain the longitude and latitude data
head(rec_sf)
## Simple feature collection with 6 features and 21 fields
## geometry type: POINT
## dimension: XY
## bbox: xmin: -83.8974 ymin: 43.74216 xmax: -82.50791 ymax: 45.97745
## epsg (SRID): NA
## proj4string: NA
## # A tibble: 6 x 22
## station glatos_array station_no consecutive_dep… intend_lat intend_long
## <chr> <chr> <dbl> <dbl> <lgl> <lgl>
## 1 WHT-009 WHT 9 1 NA NA
## 2 FDT-001 FDT 1 2 NA NA
## 3 FDT-004 FDT 4 2 NA NA
## 4 FDT-003 FDT 3 2 NA NA
## 5 FDT-002 FDT 2 2 NA NA
## 6 DTR-001 DTR 1 2 NA NA
## # … with 16 more variables: recover_lat <lgl>, recover_long <lgl>,
## # deploy_date_time <dttm>, recover_date_time <dttm>, bottom_depth <dbl>,
## # riser_length <dbl>, instrument_depth <dbl>, ins_model_no <chr>,
## # glatos_ins_frequency <dbl>, ins_serial_no <dbl>, deployed_by <lgl>,
## # comments <lgl>, glatos_seasonal <chr>, glatos_project <chr>,
## # glatos_vps <chr>, geometry <POINT>
plot(rec_sf["glatos_array"])

rec_sf <-
Rxdeploy %>%
st_as_sf(coords = c("deploy_long", "deploy_lat"),
crs = 4326) ## specify your epsg code in the crs parameter
rec_sf
## Simple feature collection with 898 features and 21 fields
## geometry type: POINT
## dimension: XY
## bbox: xmin: -84.762 ymin: 41.56911 xmax: -79.32217 ymax: 46.54273
## epsg (SRID): 4326
## proj4string: +proj=longlat +datum=WGS84 +no_defs
## # A tibble: 898 x 22
## station glatos_array station_no consecutive_dep… intend_lat intend_long
## <chr> <chr> <dbl> <dbl> <lgl> <lgl>
## 1 WHT-009 WHT 9 1 NA NA
## 2 FDT-001 FDT 1 2 NA NA
## 3 FDT-004 FDT 4 2 NA NA
## 4 FDT-003 FDT 3 2 NA NA
## 5 FDT-002 FDT 2 2 NA NA
## 6 DTR-001 DTR 1 2 NA NA
## 7 DTR-002 DTR 2 2 NA NA
## 8 DTR-003 DTR 3 2 NA NA
## 9 DTR-004 DTR 4 2 NA NA
## 10 LVD-001 LVD 1 1 NA NA
## # … with 888 more rows, and 16 more variables: recover_lat <lgl>,
## # recover_long <lgl>, deploy_date_time <dttm>, recover_date_time <dttm>,
## # bottom_depth <dbl>, riser_length <dbl>, instrument_depth <dbl>,
## # ins_model_no <chr>, glatos_ins_frequency <dbl>, ins_serial_no <dbl>,
## # deployed_by <lgl>, comments <lgl>, glatos_seasonal <chr>,
## # glatos_project <chr>, glatos_vps <chr>, geometry <POINT [°]>
plot(rec_sf["glatos_array"])

mapview(rec_sf)
mapview(rec_sf,
zcol = "glatos_project",
burst = TRUE)